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An Approach for Processing the Real-time Monitoring Data of Water Quality and Its Application in Water Quality Evaluating

  • Shiliang Gao
  • Linsong Zhang
  • Jingneng NiEmail author
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1001)

Abstract

The processing of monitored data is the key to water quality assessment and plays an important role in the development and application of water quality assessment models. Base on fuzzy random variable, an approach for processing the monitored data of water quality is proposed in this paper. In which, all monitored data information of water quality are included into a fuzzy random variable via an interval and a probability density function. Embedded into a one-factor assessment model, the proposed approach is applied to assess water quality in Chaohu lake, located in eastern China, to verify its feasibility. The results show that the approach proposed in the research has the advantage of reducing the loss of water quality information.

Keywords

Monitored data Fuzzy random variable Fuzzy interval Probability density function Water quality assessment 

Notes

Acknowledgments

The research is supported by the Quality Engineering Foundation of Hefei University (Grant No. 2017jyxm016), also supported by the Social Science Foundation of Anhui Province (Grant No. AHSKY2017D83),the Talent Foundation of Hefei University (Grant No. 16-17RC27),the Major Program for Humanities and Social Sciences of Education Bureau of Anhui Province (Grant No. SK2018ZD048). The authors thank the reviewers’ valuable comments and editors’ constructive suggestions, which will greatly improve the quality of this paper.

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Department of Mathematics and PhysicsHefei UniversityHefeiPeople’s Republic of China
  2. 2.Mathematical Modeling LaboratoryHefei UniversityHefeiPeople’s Republic of China

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